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The rapid development of teacher informatization has become a major highlight in current teaching. The information system under adaptive conditions has become the key to the reform of the intelligent era. The goal of this study is to design and implement an adaptive evaluation system for teachers’ information-based teaching ability, aiming at improving ability to meet the needs of modern education. This system analyzes the level of acceptance under key learning technologies. It combines elements by learning and analyzing their impact on general forms. It aims to analyze the rule algorithm dataset in a single machine environment. By analyzing multiple sets of different datasets, it calculates the number of key technologies that appear together in the same report based on the key technology word matrix. A co-occurrence matrix is constructed. The system adopts an advanced adaptive algorithm, which can conduct personalized assessments according to the actual ability and needs of teachers, so as to provide more accurate and effective feedback, help teachers understand their own advantages and disadvantages, and formulate more targeted promotion strategies. In the process of system design, the detailed requirement analysis is carried out first, and the function and performance requirements of the system are clarified. Then, we design the architecture of the system and determine the main modules and functions of the system. The function module is designed and the system is implemented. Through the practical application and effect evaluation of the system, we find that the system has high effectiveness and practicability. It can not only help teachers understand their own level of information-based teaching ability and provide personalized suggestions for improvement, but also provide decision support for education administrators and promote the development of education based on information. We expect that this system can play a greater role in the future education practice and promote the further development of education informatization.

The design of atomic force microscopy (AFM) with high resolution is introduced in this paper. Mainly, we have developed the system design of the apparatus based on tunneling. AFM.IPC-208B, this kind of apparatus combines scanning tunnel microscopy (STM) and AFM availability, and its lens body with original frame enhances the capability of the machine. In order to analyze the performance of AFM.IPC-208B, as a new tool in the field of Life Science, we make use of the system to study natural mica and molecular protein structures of Cattle-insulin and human antibody immunoglobulin G (IgG) coupled with staphylococcus protein A (SPA). As the results of new applications, the resolution of AFM.IPC-208B is proved to be 0.1 nm, and these nanometer measurement results provide much valuable information for the study of small molecular proteins and HIV experiments.

E-commerce retailers face the challenge to assemble a large number of time-critical picking orders. Common parts-to-picker autonomous intelligent warehouses such as automated vehicle storage and retrieval system and robotic mobile fulfillment system are often a little ill-suited for these prerequisites. A mixed-robotic fulfillment system is a hybrid robot picking system based on multi-device collaboration. It is a fusion innovation of traditional automated vehicle storage and retrieval system and robotic mobile fulfillment system. This paper comprehensively considers the characteristics of the system and customer demand, through the construction of a queuing network model to evaluate the performance of the system. A series of problems such as order service time, throughput capacity, and vehicle quantity configuration are analyzed experimentally. The validity of the model is verified by a simulation model.

Resource sharing is a very complex task in system design because it may induce undesirable properties such as deadlocks and overflows. This paper proposes a method for handling this task. Resource sharing is formulated as a place fusion on a Petri net specification that satisfies a designated set of properties and includes some duplicated places representing accesses to the resources. If this fusion satisfies some conditions, the obtained net will preserve the original properties after the incorporation of resource sharing. This paper considers two classes of property-preserving place fusions. Each class specifies the Petri net type to be used, the structural relationship among the resource places and possibly some additional conditions for the place fusion to preserve a designated set of properties. As an illustration, these place fusion approaches are applied to solve a resource sharing problem in the design of manufacturing systems.

System assembly is one of the major issues in engineering complex component-based systems. This is especially true when heterogeneous, COTS and GOTS distributed systems, typical in industrial applications, are involved. The goal of system assembly is not only to make constituent components work together, but also to ensure that the components as a whole behave consistently and guarantee certain end-to-end properties. Despite recent advances, there is a lack of understanding about software composability, as well as theory and techniques for checking and verifying component-based systems. A theory of software system constraints about components, their environment and about system as a whole is the necessary foundation toward solid understanding of the composability of component-based systems. In this paper, we present a systematic approach for constraint specification and constraint propagation in concert with design refinement with a novel technique to ensure consistency between system-wide and component constraints in a design composition process of component-based systems. The consistent constraint propagation is used in our approach to drive progressive verification of the design. It allows us to verify overall design composition without interference of internal details of component designs. Verification is done separately at architectural and component levels without having to compose results of component analyses. A component can be safely replaced with alternative design without re-verifying the overall system composition so long as the replacement conforms to the corresponding interface and component constraint(s).

European Railway Traffic Management System/European Train Control System (ERTMS/ETCS) is a recent standard aimed at improving performance, safety and inter-operability of modern railways. In order to be compliant to ERTMS/ETCS, a railway signalling system must meet strict nonfunctional requirements on system level failure modes. In this paper, a multiformalism model is employed to perform an availability analysis of an ERTMS/ETCS reference architecture at early phases of its development cycle. At this aim, a bottom-up analysis is performed from subsystem failure models (expressed by means of Generalized Stochastic Petri Nets, Fault Trees and Repairable Fault Trees) up to the overall system model. The modular approach, here used, allows to evaluate the influence of basic design parameters on the probability of system-level failure modes and demonstrates that system availability is within the bound required by the ERTMS/ETCS specification. The results show that the multiformalism modeling approach helps to cope with complexity, eases the verification of availability requirements and can be successfully applied to the analysis of complex critical systems.

Workflow management systems (WfMSs) also known as business process management systems (BPMSs) are increasingly popular in today’s large organizations. In spite of this popularity, many processes are still supported by ad hoc systems based, for example, on spreadsheets and homegrown databases. In particular, there is a lack of flexible process automation approaches that are able to bridge the gap between these ad hoc solutions and large-scale systems. This paper reports on a flexible WfMS and approach that blends formal and informal workflow modeling and execution, thus supporting different types of processes. We validate our work by discussing its design and implementation, and by analyzing its use in four different use cases within Siemens business units. We also discuss the role of action items as important flexibility mechanisms behind our model. Showing its ability to handle exceptions and ad hoc workflows.

The traditional teaching system uses local area network to realize online teaching, which leads to high stability and hardware load of the teaching system and makes it difficult to meet the teaching demand. To solve the above problems, a dance movement distance learning system based on wireless network communication technology is designed. On the B/S architecture, the hardware control module and communication module of the system are designed. The fuzzy set principle is used to evaluate the students’ dance cognitive ability, so as to personalize the recommended teaching contents. The teaching video is compressed according to H.264/AV compression standard to reduce the system transmission and processing load. The system functionality test results show that the maximum transmission packet loss rate of the designed system is 8.3%, and the lost data does not interfere with teaching, has low computer memory consumption, and has superior performance.

According to the existing literature, the existing engineering ideological and political curriculum distance education system has the problems of long response time and few concurrent users, which cannot meet the development needs of the professional talents of electronic engineering. Therefore, the design and research of the long-distance education system of the ideological and political course of electronic engineering specialty dependent on big data is proposed. Based on the analysis of the demand of distance education system, the overall structure of the distance education system is designed. The design of the system business functions mainly includes login verification module design, instant communication module design, online classroom module design, video answer module design and video back-view module design, and design the server cluster load balancing strategy according to big data technology, so as to realize the operation of the remote education system of the ideological and political courses of electronic engineering. The design system is shorter than response time while compared with existing system. and the number of users is more. It is fully proved that the design system has better application performance.

In view of the longtime interactive English–Chinese translation system, an interactive English–Chinese translation system based on Griffin–Lim algorithm (GLA) is proposed. The hardware design of the system is completed by the hardware structure design, the interactive English–Chinese translation memory design and the interactive English–Chinese translation retrieval system design. Through analysing the semantic characteristics of interactive English–Chinese translation, constructing interactive English–Chinese translation database and designing interactive English–Chinese translation process, the system software design is completed and interactive English–Chinese translation is realised. The results of the system test show that the interactive English–Chinese translation system based on the GLA algorithm cannot only shorten the time of interactive English–Chinese translation, but also accelerate the response speed of the translation system, and greatly improve the overall performance of the interactive English–Chinese translation system.

Nowadays, with the continuous change and innovation of teaching methods in Colleges and universities, the curriculum system of students is also constantly enriched and developed. Therefore, people’s requirements for teaching management and teaching system are also improving. Physical education curriculum is usually based on outdoor teaching, and some schools have not established a complete teaching system. Therefore, the interactive teaching system of physical training based on artificial intelligence is designed. First of all, through the construction of the interactive teaching system of the total control circuit, determine the corresponding circuit address decoding, improve the audio control circuit, associated video connection interactive drive three parts, the intelligent sports training interactive system hardware design. Then, through the creation of intelligent training function module, the design of training database and the realisation of effective training and teaching of intelligent sports, the software design of intelligent sports training interactive system is carried out. Finally, through the test of the system, to verify the corresponding effect, further improve the relevant system, make it more safe and accurate, improve the efficiency of sports training interactive system, enhance the integrity of the teaching process.

Structured meshes are becoming increasingly popular as a discretization technique in industries where solution accuracy is of paramount importance. However, generating structured meshes directly on the model surface presents a challenge. Consequently, many researchers are now exploring mapping methods for structured mesh generation. In this context, parameterization algorithms are vital as they map the model surface from 3D space to a 2D parametric domain. Existing parameterization algorithms, despite their advancements, still face limitations in preserving symmetry information from the input model. To address this issue, we propose a symmetry preserving parameterization algorithm based on geometric constraint. This algorithm utilizes plane reflection symmetry transformation to identify the main symmetry plane of the model and calculate the symmetry factor. Based on the fixed points and the symmetry factor, a conformal parametric symmetry plane is obtained. Furthermore, we develop a surface structured mesh generation system to provide engineers with a tool that can rapidly generate meshes. Experimental results demonstrate that our proposed algorithm achieves higher quality results compared to other parameterization algorithms.

Vision-based sensors are a key component for robot-systems, where many tasks depend on image data. Realtime control constraints bind a lot of processing power for only a single sensor modality. Dedicated and distributed processing resources are the "natural" solution to overcome this limitation. This paper presents experiments, using embedded processors as well as dedicated hardware, to execute various image (pre)processing tasks. Architectural concepts and requirements for intelligent vision systems have been acquired.

Recent progress in Web Real-Time Communication (WebRTC) promotes multi-apps environment by creating islands of communication apps where users of one website or service cannot easily communicate with those of another. We describe the architecture and implementation of a multi-platform system to do user reachability in multiple communication services where users decide how they want to be reached on multiple apps, e.g. in an organization that has voice-over-IP, web conferencing and messaging from different vendors. We argue for user and endpoint driven reachability policies and cross-app interactions, instead of pair-wise service federation or global location service. Our architecture separates the user contacts from reachability apps, and has several independent and non-interoperable WebRTC-based apps for two-way and multi-party multimedia communication. Our software is implemented using HTML5 and JavaScript, and using a cross-platform development tool, runs as native apps on mobile as well as personal computers. Our flexible implementation can be used for enterprise or personal communications, or as a white-labeled app for consumers of a business.

Artificial intelligence (AI) faces a trifecta of grand challenges: the Energy Wall, the Alignment Problem and the Leap from Narrow AI to AGI. Contemporary AI solutions consume unsustainable amounts of energy during model training and daily operations. Making things worse, the amount of computation required to train each new AI model has been doubling every 2 months since 2020, directly translating to unprecedented increases in energy consumption. The leap from AI to AGI requires multiple functional subsystems operating in a balanced manner, which requires a system architecture. However, the current approach to AI lacks system design; even though system characteristics play a key role in the human brain; from the way it processes information to how it makes decisions. In this paper, we posit that system design is the missing piece in overcoming current AI the grand challenges. We present a Systematic Approach to AGI (SAGI) that utilizes system design principles to overcome the energy wall and the alignment challenges. This paper asserts that artificial intelligence can be realized through a multiplicity of design-specific pathways, rather than a singular, overarching AGI architecture. AGI systems may exhibit diverse architectural configurations and capabilities, contingent upon their intended use cases. We argue that AI alignment, the most difficult among the grand challenges, is not attainable without a way to reflect the complexity of the human moral system and its subsystems in the AGI architectures. We claim that AGI approaches such as symbolicism, connectionism and others are not fundamental to AGI but emergent from the system design processes. Hence, we focus on employing system design principles as a guiding framework, rather than solely concentrating on a universal AGI architecture.

We review Discrete-Event system Specification (DEVS) in the context of Model-based Systems Engineering (MBSE) and discuss an application of DEVS methodology to MBSE. We outline support for an envisioned MBSE development cycle of DEVS top-to-bottom MBSE capability and offer an example of mapping UML activity diagrams into executable activity-based DEVS models. We close with conclusions and future research directions.

In this paper, we explore a novel multi-mode hybrid Unmanned Aerial Vehicle (UAV). We combine a tailless fixed-wing with a dual-wing monocopter such that the craft’s propulsion systems and aerodynamic surfaces are fully utilized in both a horizontal cruising mode and a vertical hovering mode. This maximizes the structural efficiency across the flight envelope, thereby reducing drag and unused mass while airborne in either flight mode. This UAV is also designed such that the transition between the two flight modes can be executed in mid-air, using only its existing flight actuators and sensors — there are no transition specific actuators. Using two prototypes, the foundational design and control of the system is established; the first explores the hovering mode characteristics of the unique dual-wing monocopter configuration, while the second explores the full multi-mode capabilities of the combined platform. In addition to analytical simulations, the prototypes are experimentally evaluated and assessed to demonstrate the feasibility, viability and potential of this multi-mode aerial robot design.

Since monitoring one’s ovulation in an accurate manner is significant to the physiological health of women during the reproductive period, it’s better to combine family healthcare and smart home devices to work out feasible ways of ovulation monitoring. A study found that the value of LH(luteinizing hormone) in women’s urine was significantly correlated with ovulation. Therefore, by measuring the peak of LH, the ovulation status of women could be accurately monitored. In this study, a monitoring system was designed to determine ovulation status by detecting LH (luteinizing hormone) value in female urine. This monitoring system was integrated with the household toilet to realize the real-time and accurate monitoring of ovulation status of female individual. In the aspect of hardware, the device appearance, the detection device structure and the micro-control electronic device were designed by applying the Internet of things technology, to help women obtain ovulation information in a convenient and stable manner. Whereas in the aspect of software, the author analyzed the monitoring data based on computer algorithm, developed mobile application, and established the individual longitudinal database with multiple detection values as background data, so as to predict ovulation activity and evaluate ovulation patterns. It would help women track their ovulation more accurately, prevent and indicate gynecological reproductive diseases, and can serve as a supplementary basis for medical diagnosis and treatment results.

At present, the supply chain financing model is still in the initial stage of development in China. To effectively improve the operation level of the supply chain financing model and make it paramount in the financing of small and medium-sized enterprises, blockchain technology is introduced, and the overall structure of the system is firstly designed comprehensively, and then combined with the supply chain. According to the actual needs of financing, how to realize the main function modules of the supply chain financing system is discussed, and finally the system is tested in practice.

In order to promote the construction and development of rural energy Internet, this paper designs corresponding business models for the three stages of rural energy Internet investment - construction - operation, and establishes cost and value measurement models. Based on the actual data in Shandong, five different scenarios are set up to measure the cost and value, and the best means to improve the economic efficiency of rural industries are identified through sensitivity analysis. The results of the example show that considering multiple benefits can bring a better economy to the rural energy industry, and increasing the percentage of direct energy supply is the best way to improve the economy of the rural energy industry.